Ram C. Dahiya

962 citations
42 papers · 700 indexed · h-index 16
Topics
Statistical Distribution Estimation and Applications (24 papers)Bayesian Methods and Mixture Models (14 papers)Advanced Statistical Methods and Models (13 papers)

In The Last Decade

Ram C. Dahiya

42 papers receiving 634 citations

Peers

Ram C. Dahiya
Comparison fields: 5 of 98
  • Statistics and Probability 447
  • Artificial Intelligence 160
  • Safety, Risk, Reliability and Quality 142
  • Statistics, Probability and Uncertainty 121
  • Software 114
Replace A. R. Nematollahi with:
A. R. Nematollahi Iran
Jian Shi China
J. C. Naylor United Kingdom
Satya D. Dubey United States
Albert H. Moore United States
Hare Krishna India
Vartan Choulakian Canada
Ronald E. Glaser United States
Nicholas R. Farnum United States
N. Unnikrishnan Nair India
Ram C. Dahiya relative to A. R. Nematollahi Iran A. R. Nematollahi's profile →
Citations per field
00.5×3.9×
A. R. Nematollahi · 1×
Citations per year

Countries citing papers authored by Ram C. Dahiya

Since Specialization
Citations

This map shows the geographic impact of Ram C. Dahiya's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ram C. Dahiya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ram C. Dahiya more than expected).

Fields of papers citing papers by Ram C. Dahiya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ram C. Dahiya. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ram C. Dahiya. The network helps show where Ram C. Dahiya may publish in the future.

Co-authorship network of co-authors of Ram C. Dahiya

This figure shows the co-authorship network connecting the top 25 collaborators of Ram C. Dahiya. A scholar is included among the top collaborators of Ram C. Dahiya based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ram C. Dahiya. Ram C. Dahiya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 21
2 1
3 1
4 18
5 7
6 14
7 13
8 5
9 22
10 19
11 11
12 3
13 4
14 28
15 9
16 15
17 47
18 15
19 11
20 4

About Ram C. Dahiya

Ram C. Dahiya is a scholar working on Statistics and Probability, Software and Artificial Intelligence, having authored 42 papers that have together received 700 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (24 papers), Bayesian Methods and Mixture Models (14 papers) and Advanced Statistical Methods and Models (13 papers). The work is most often cited by research in Statistics and Probability (447 citations), Software (114 citations) and Statistics, Probability and Uncertainty (121 citations). Ram C. Dahiya has collaborated with scholars based in United States, Ghana and Indonesia. Frequent co-authors include John Gurland, Syed Akhter Hossain, Alan J. Gross, Saul Blumenthal, Ramesh M. Korwar, Irwin Guttman, R. Kleyle, Raymond W. Alden, Robert J. Young and N. Rao Chaganty. Their work appears in journals such as Journal of the American Statistical Association, Technometrics and Biometrics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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